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A Modified Approach for Node Deployment

in Wireless SensorNetworks

Shruti Prabha Shaktawat Tapan Nahar

M-tech Scholar*, Digital Communication M-tech Scholar*, Digital Communication

Poornima College of Engineering Poornima College of EngineeringJaipur, India Jaipur, India

shrutishaktawat@gmail.com tapanvnahar@gmail.com

Abstract: A wireless sensor network consists of hundreds orthousands of low cost nodes which could either have a fixed

location or can be randomly deployed to monitor the environment.

The sensors sense environmental changes and report them to the

nodes over flexible network architecture. The foremost challenge

faced by micro sensor nodes is the need for significant reduction in

energy consumption to ensure their longer usability. A power-

aware methodology emphasizes the scalability of energy

consumption by considering factors such as available resources,

event frequency and desired output quality, at all levels of the

system hierarchy. In this paper we have analyzed the relationship

between the energy consumption and the node deployment strategy.

To gather information more efficiently, wireless sensor networks

are partitioned into clusters. Here we also use the concept of duty

cycling to reduce the idle listening by periodically putting nodes

into sleep state. In the sleep state, the radio is completely turned off.

Finally, the aim of energy efficient wireless sensor network can be

achieved.

Keywords: Wireless sensor networks (WSNs), Clustering, Dutycycling, Cluster head, Node deploymentand Energy Efficiency.

I.

I. INTRODUCTIONThe concept of wireless sensor networks is based on

digital electronics, micro-electro-mechanical systems (MEMS)

and wireless communication technology [1]. Wireless sensor

networks typically consist of a large number of sensor nodes,

which are deployed inside the phenomenon to sense. Nodeshelp to sense the phenomenon of interest, to process the

collected data and to communicate the data to the user through

a set of sink nodes. Wireless sensor networks have found

military applications in equipment monitoring, battlefield

surveillance, reconnaissance and nuclear/chemical/biological

attack detection [2]. They have also found wide civilian

applications in environmental monitoring, disaster warning,medicine and home automation. The idea of deploying

wireless sensor networks in the ocean to sense, survey and

monitor phenomenon of interest is attractive to navies,maritime operators, environment monitoring agencies,

offshore industry and scientific researchers. [1, 2]

A wireless sensor network (WSN) consists of a large

number of tiny sensor nodes (as shown in fig. 1) deployed

over a geographical area also known as sensor field, each node

is a low-power device that integrates computing, wireless

communication and sensing abilities. In Wireless sensornetwork nodes arrange themselves in form of clusters and

networks and perform an assigned monitoring task without

any human intervention and resolutions that are difficult [3]

Sensor nodes are able to sense physical environmentainformation, process the acquired data both at unit and cluster

level and send the result to the cluster [4] and one or more

collection points named as sinks or base stations. [5]

Figure 1: A typical sensor network architecture.

However, energy consumption still remains one of the

main obstacles to the diffusion of this technology, especially

in application scenarios where a long network lifetime and a

high quality of services are required. This paper has 4

sections. Section I deals with the basic introduction of wsn. In

section II schemes of power management is discussed. SectionIII highlights the proposed scheme and its merits. Overal

finding and opinion is concluded in section IV.

II. POWER MANAGEMENT IN WSNs

Wireless sensor node consists of four main components

[6]: (i) a sensing subsystem including one or more sensors

(with associated analog-to-digital converters) for data

acquisition; (ii) a processing subsystem including a micro-

controller and memory for local data processing; (iii) a radio

subsystem for wireless data communication; and (iv) a powersupply unit. Depending on the specific application, sensor

nodes may also include some additional components such as alocation finding system to determine their position, a

mobilizer to change their location or configuration (e.g.antennas orientation). The architecture of a typical wirelesssensor node is shown in figure 2. [3, 6]

Internet

User

Sink NodeSensor Field

Sensor Node

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Figure 2: Architecture of a typical wireless sensor node.

Wireless sensor networks consume energy during sensing,

processing and transmitting stage.[7] And to reduce the overall

energy consumption of the network and to make the system

life-long different power management (PM) techniques areused on different levels of the network.[8]

III. PROPOSED SCHEME:

There are many ways in which sensor nodes can be deployed

in the sensing field. Here we are giving a hybrid approach fornode deployment i.e. the nodes will be deployed in a special

manner to reduce the power consumption. Previously nodes

were randomly distributed in a sensing field and all the nodes

were remain active during their complete life cycle and send

the data to the base station individually or jointly according to

the topology used.

Here we use the combination of clustering techniqueand duty cycling technique to make a new approach for sensor

deployment in sensing field which improves the life time of

nodes. Firstly we deploy the nodes in a regular fashion and for

this we suggest the two approaches which are based on the

hexagonal geometry. In first scheme inside the hexagonal

geometry we arranged the nodes in a grid mode and in second

scheme we divide the hexagon in six equilateral triangles.

These two schemes as shown in fig. 3 cover the maximumarea and also reduce the adjacent cluster interference.

Now in these hexagonal clusters a cluster head (CH)

is chosen on the basis of its energy. Each sensor node

Now in these hexagonal clusters a cluster head (CH) is chosen

on the basis of its energy. Each sensor node chooses a random

number between 0 and 1. If this value is lower than thethreshold value the sensor node becomes a cluster-head. After

CH selection cluster heads broadcast their selection to al

nodes, all nodes choose their nearest cluster head by signal

strength and send their data to the cluster head. The cluster

heads assign a TDMA schedule for their cluster members

Here only one node is kept active and other nodes will remainsoff. After this, cluster head performs data aggregation and the

aggregated data is send to the base station.

After a certain period of time all nodes become active and nowa new cluster head is selected on the basis of its energy. The

nodes which were already cluster head will not be able to take

part again.

IV. CONCLUSION

The proposed scheme may resolve the problem of overlapping

in clusters and minimizes the energy consumption. Thehexagonal geometry covers the maximum area and reduces the

adjacent cluster interference. Finally keeping one node active

at a time reduces the overall energy consumption. By this

scheme all nodes become cluster head at least one time.

REFERENCES:

[1]I. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. Wireless

sensor networks: a survey. Computer networks, 38(4):393422, 2002.

[2] I. F. Akyildiz, T. Melodia, K.R. Chowdhury, A Survey on Wireles

Multimedia Sensor Networks, Computer Networks, Vol. 51, Issue 4, pp921-960, March 14, 2007.

[3]G. Anastasi, M. Conti, M. Di Francesco, A. Passarella, Energy

Conservation in Wireless Sensor Networks, Ad Hoc Networks.

[4]S. Faye and J. F. Myoupo, An ultra hierarchical clustering based secure

aggregation protocol for wireless sensor networks,Advances in Information

Sciences and Service Sciences, vol. 3, no. 9, pp. 309319, 2011.

[5] A. Abbasi and M. Younis, A survey on clustering algorithms for wirelessensor networks, Computer Communications, vol. 30, pp.2826-2841

October 2007.

[6]G. Anastasi, M. Conti, M. Di Francesco, A. Passarella, How to Prolong

the Lifetime of Wireless Sensor Networks, Chapter 6 in Mobile Ad Hoc andPervasive Communications, (M. Denko and L. Yang, Editors), American

Scientific Publishers.

[7]R. Jurdak, A. G. Ruzzelli and G. M. P. OHare, Radio Sleep Mode

Optimization in Wireless Sensor Networks, in IEEE Trans. on Mobile

Computing, Vol. 9, No. 7, July 2010, pp. 955968.

[8] V. Mhatre and C. Rosenberg, Design guidelines for wireless senso

networks: communication, clustering and aggregation,Ad Hoc Networks

vol. 2, no. 1, pp. 4563, 2004.

Figure 3: Suggested Schemes for Node Deployment

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